基于GAT-Informer的采空区煤自燃温度预测模型
Prediction model for spontaneous combustion temperature in goaf based on GAT-Informer
-
摘要: 针对工作面采空区煤自燃温度预测精度不高的问题,在有效提取煤自燃监测数据时空特征的基础上,提出了一种基于图注意力网络(GAT)和Informer模型的采空区煤自燃温度预测模型(GAT-Informer)。首先使用随机森林回归方法和Savitzky-Golay滤波器对煤自燃监测数据中的异常值和噪声进行预处理。其次,基于历史监测数据,采用GAT模块提取各监测点间的空间特征;采用Informer捕获数据之间的时间特征;最后,在融合时空特征的基础上对煤温进行预测。实验结果表明,基于GAT-Informer的煤自燃温度预测模型在多测点监测数据上的预测结果要优于单一的RNN,LSTM,GRU和Informer预测模型,在6个监测点位上,MSE分别平均降低了15.70%、22.15%、25.46%、36.48%,MAE分别平均降低了16.00%、14.58%、20.29%、26.26%,表明GAT-Informer模型能有效提高煤温预测精度、预防采空区煤自燃带来的灾害,对煤矿的安全生产具有重要的现实意义。Abstract: Aiming at the problem of low accuracy in predicting the spontaneous combustion temperature of coal in goaf, a GAT-Informer model based on graph attention network (GAT) and Informer model is proposed to effectively extract the spatiotemporal characteristics of coal spontaneous combustion monitoring data. Firstly, the random forest regression method and Savitzky Golay filter are used to preprocess the outliers and noise in the coal spontaneous combustion monitoring data. Secondly, based on historical monitoring data, the GAT module is used to extract spatial features between each monitoring point. Then, the Informer model is used to capture the temporal characteristics between the data. Finally, based on the fusion of spatiotemporal features, the coal temperature is predicted. The experimental results show that the coal spontaneous combustion temperature prediction model based on GAT-Informer outperforms single RNN, LSTM, GRU, and Informer prediction models on multi monitoring data. At six monitoring points, the MSE decreased by an average of 15.70%, 22.15%, 25.46%, and 36.48%, and the MAE decreased by an average of 16.00%, 14.58%, 20.29%, and 26.26%, respectively. This indicates that the GAT Informer model can effectively improve the accuracy of coal temperature prediction, prevent disasters caused by coal spontaneous combustion in goaf areas, and has important practical significance for the safety production of coal mines.
-
Key words:
- Coal spontaneous combustion /
- Time series /
- GAT /
- Informer /
- Coal temperature prediction
点击查看大图
计量
- 文章访问数: 10
- HTML全文浏览量: 2
- 被引次数: 0